Exploration of Convolutional Neural Network models for source code classification

Francesco Barchi, Emanuele Parisi, Gianvito Urgese, Elisa Ficarra, Andrea Acquaviva

Abstract: Highlights•CNN-based source code classification is effective in terms of accuracy and speed-up.•CNNs are more robust than LSTM with respect to hyperparameters and filtering methods.•CNNs show a 4-7x shorter training time over LSTM for text and source code analysis.•LLVM-IR code analysis is independent of the language and the underlying hardware.